Intelligent construction method and system for hardware equipment platform of transformer substation

Abstract

The invention provides an intelligent construction method and system for a substation hardware equipment platform, and the method achieves the unified management of data and models through the construction of a standardized hardware equipment basic platform. An intelligent operation and maintenance system is built, online infrared and manual dual modes are adopted for temperature measurement, and multi-stage temperature threshold values are set for real-time early warning; an intelligent maintenance system is constructed, a standard operation card is pushed according to a ten-step method, and digital operation is carried out in combination with intelligent wearing; building a hardware fitting digital twinborn model, fusing three-dimensional visualization and temperature simulation, and realizing precise positioning and temperature rise prediction of hardware fitting equipment; and performing'green / yellow / red 'three-color dynamic rating on the hardware fitting by applying an artificial intelligence technology, and intelligently recommending an optimal maintenance strategy. Compared with the prior art, a whole-process closed-loop management system of'monitoring-early warning-diagnosis-disposal 'is constructed, and the quality, efficiency and safety level of equipment management are improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of electrical engineering information technology, and particularly relates to a substation hardware equipment platform intelligent construction method and system. BACKGROUND

[0002] In the field of substation hardware equipment management, the existing hardware equipment management system generally has the problems of single function and insufficient intelligence, and specifically has the following problems:

[0003] (1) The existing system is mainly limited to real-time monitoring of hardware temperature, lacks longitudinal tracking analysis of historical temperature data of the same equipment, and cannot realize horizontal temperature comparison between multiple equipment, making it difficult for operation personnel to fully grasp the equipment state.

[0004] (2) The existing system only sets a fixed threshold alarm in temperature abnormality early warning, neither establishes an intelligent evaluation model based on the fusion of multiple parameters such as temperature rise rate, environmental temperature and load current, nor lacks equipment state degradation trend prediction function, so that the operation and maintenance decision still highly depends on manual experience.

[0005] (3) Due to the lack of accurate prediction and early identification ability of equipment state, the existing system often leads to hidden danger discovery lag, affecting the safe operation of power grid.

[0006] (4) The existing system cannot realize accurate positioning of hardware equipment, and has the problem of "many points and difficult positioning", which seriously affects the field maintenance efficiency.

[0007] (5) The traditional management method has been difficult to meet the demand of modern power grid for accurate control of equipment state, and it is urgent to build an intelligent hardware management platform integrating real-time monitoring, intelligent analysis, state evaluation and predictive maintenance. SUMMARY

[0008] The application provides a substation hardware equipment platform intelligent construction method and system, aiming to solve the problems of data isolation, non-uniform model, simple early warning mechanism, hidden danger discovery lag and positioning difficulty in the prior art.

[0009] Technical scheme: The application provides a substation hardware equipment platform intelligent construction method, comprising:

[0010] A standardized hardware equipment basic platform is constructed to manage hardware equipment account data model; the hardware equipment data model includes hardware number, type, material and current carrying capacity;

[0011] An intelligent operation and maintenance system is constructed to collect substation hardware temperature data in full coverage and set multiple temperature thresholds for real-time early warning, identify heating hazards through trend analysis, and monitor the hazards;

[0012] An intelligent maintenance system is constructed, the straight resistance and torque parameters of the fitting device are automatically collected by the mobile terminal and uploaded, the standard operation card is pushed, the digital operation is carried out in combination with the intelligent wearing, the whole cycle data tracing of the maintenance is established, and the fault diagnosis support is provided relying on the case library;

[0013] A fitting digital twin model is built, three-dimensional visualization and temperature simulation are fused, a three-dimensional model is constructed, the position of the fitting device is located by mapping the two-dimensional model and the three-dimensional model of the fitting device, and the temperature rise is predicted in combination with the load and the environmental temperature;

[0014] Artificial intelligence technology is applied, the fitting is dynamically rated in three colors of "green / yellow / red" based on multi-dimensional data, and the optimal maintenance strategy is intelligently recommended in combination with the fault library.

[0015] Further, the standard fitting device basic platform is constructed, the data is entered from the mobile terminal, and the data is standardized, the two-dimensional model is established, the two-dimensional model is associated with the standardized fitting device account data, operation data and maintenance data, and the standardized account data, operation data and maintenance data of the fitting device are displayed on the platform.

[0016] Further, the fitting digital twin model comprises:

[0017] A three-dimensional digital twin model is constructed, the three-dimensional digital twin model is dynamically associated with the fitting account data and the operation data; the two-dimensional-three-dimensional space mapping technology is adopted, the same physical feature points are marked in the two-dimensional model and the three-dimensional digital twin model of the fitting device, the accurate positions of the two-dimensional pixel coordinate system (u, v) and the three-dimensional coordinate system (X, Y, Z) are obtained, the conversion relationship is calculated through the orthogonal projection matrix, the mathematical mapping model is established, and any point on the two-dimensional model is projected to the corresponding position in the three-dimensional space through the model;

[0018] In combination with the power load and the environmental temperature parameters, the temperature field simulation technology in the digital twin is used to simulate the heat generation and transmission process of the fitting device under the current thermal effect and environmental heat dissipation effect, to dynamically generate the temperature field distribution of the fitting device under different working conditions, to track the temperature change curve of the key position based on the simulation results, to deduce the future temperature trend of the position in combination with the heat accumulation law, and to identify the overheating risk points possibly caused by local heat concentration in advance.

[0019] Further, the artificial intelligence technology is applied, the health status of the fitting is dynamically rated in three colors of "green / yellow / red" based on the temperature, current and historical operation data of the fitting; the differential detection is carried out according to the rating results of the fitting, the optimal operation and detection scheme is intelligently recommended in combination with the state evaluation results and the fault diagnosis model, relying on the defect risk library and the maintenance strategy library, including the maintenance project, type and period.

[0020] This invention also provides an intelligent construction system for a substation hardware equipment platform, comprising:

[0021] The hardware standardization module is used to build a standardized hardware equipment basic platform for managing the hardware equipment ledger data model; the hardware equipment data model includes hardware number, type, material, and current carrying capacity;

[0022] The temperature monitoring module is used to build an intelligent operation and maintenance system. It collects temperature data of substation fittings in a comprehensive manner, sets multi-level temperature thresholds for real-time early warning, identifies potential overheating hazards through trend analysis, and monitors the hazard points.

[0023] The intelligent maintenance module is used to build an intelligent maintenance system. It automatically collects and uploads the DC resistance and torque parameters of hardware equipment through mobile terminals, pushes standard operation cards, performs digital operations in conjunction with smart wearables, establishes data traceability for the entire maintenance cycle, and provides fault diagnosis support based on a case library.

[0024] The digital twin module is used to build a digital twin model of the fittings, integrating 3D visualization and temperature simulation to construct a 3D model. By mapping the 2D and 3D models of the fittings, the location of the fittings can be determined, and temperature rise can be predicted by combining load and ambient temperature.

[0025] The intelligent assessment module applies artificial intelligence technology to dynamically rate hardware using a three-color system of "green / yellow / red" based on multi-dimensional data, and intelligently recommends the optimal maintenance strategy in conjunction with a fault database.

[0026] Furthermore, in the hardware standardization module, a standardized hardware equipment basic platform is constructed. Data is entered from a mobile terminal and the data is standardized. A two-dimensional model is established and associated with the standardized hardware equipment ledger data, operation data, and maintenance data. The standardized hardware equipment ledger data, operation data, and maintenance data are then integrated and displayed on the platform.

[0027] Furthermore, in the digital twin module, the digital twin model of the hardware includes:

[0028] A three-dimensional digital twin model is constructed, which is dynamically linked with hardware ledger data and operational data. Using two-dimensional to three-dimensional spatial mapping technology, the same physical feature points are marked in the two-dimensional model and the three-dimensional digital twin model of the hardware equipment to obtain the precise positions of the two-dimensional pixel coordinate system (u,v) and the three-dimensional coordinate system (X,Y,Z). The transformation relationship is calculated through orthogonal projection matrix to establish a mathematical mapping model, and any point on the two-dimensional model is back-projected to the corresponding position in the three-dimensional space.

[0029] In combination with power load and environmental temperature parameters, the temperature field simulation technology in digital twinning is used to simulate the heat generation and transmission process of the fitting device under the current thermal effect and environmental heat dissipation effect, dynamically generate the temperature field distribution of the fitting device under different working conditions, track the temperature change curve of the key position based on the simulation results, deduce the future temperature trend of the position according to the heat accumulation law, and identify the overheating risk points possibly caused by local heat concentration in advance.

[0030] Further, in the intelligent evaluation module, the artificial intelligence technology is applied to dynamically grade the health status of the fitting device as green / yellow / red based on the temperature, current and historical operation and maintenance data of the fitting device, different detection is performed according to the grading results of the fitting device, the optimal operation and maintenance scheme is intelligently recommended based on the state evaluation results, the fault diagnosis model, the defect risk library and the maintenance strategy library, including the maintenance project, type and cycle.

[0031] The application further provides a computer device, including a memory, a processor and a computer program stored on the memory and executable on the processor, and the processor implements the steps of the above method when executing the computer program.

[0032] The application further provides a computer readable storage medium having a computer program stored thereon, and the computer program implements the steps of the above method when executed by a processor.

[0033] Beneficial effects: The intelligent construction method and system of the transformer substation fitting device platform provided by the application can realize multi-dimensional information fusion linkage of fitting devices, online evaluation of device state, active early warning of abnormalities and intelligent diagnosis of faults, and construct a whole-process closed-loop management system of "monitoring-early warning-diagnosis-disposal". By constructing a standardized fitting device basic platform, unified management and efficient collaboration of data and models are realized. Through "online infrared + manual" dual-mode temperature measurement, combined with multi-level temperature threshold alarm and trend analysis, full-coverage collection of fitting temperature data and accurate monitoring of key points in the whole station are realized, and the identification ability of hidden heating problems is improved. Through automatic collection and one-key uploading of mobile terminal parameters such as direct resistance and torque, the standard operation card is pushed according to the "ten-step method", the operation process is standardized and data is traced throughout the cycle by combining intelligent wear, and accurate fault diagnosis is realized by relying on the case library. By constructing a high-precision three-dimensional digital twinning model, the fitting is positioned by combining two-dimensional-three-dimensional mapping technology, and the temperature rise is predicted based on load and environmental temperature, solving the problems of multiple points and difficult positioning. Through AI algorithm fusion of temperature, current and historical operation and maintenance data, the fitting is dynamically graded as green / yellow / red, and the optimal operation and maintenance scheme is intelligently recommended based on the defect risk library and the maintenance strategy library, realizing predictive maintenance, improving equipment management quality and safety level. BRIEF DESCRIPTION OF DRAWINGS

[0034] Figure 1Fig. 1 is a schematic diagram of a standardized hardware equipment base platform.

[0035] Figure 2 Fig. 4 is a flowchart of fault diagnosis.

[0036] Figure 3 Fig. 5 is a flowchart of state evaluation.

[0037] Figure 4 Fig. 6 is a flowchart of operation and maintenance strategy. DETAILED DESCRIPTION

[0038] The present application will be further clarified by the following examples and figures, which should not be taken as limiting the scope of the present application. After reading this application, those skilled in the art will appreciate modifications of the present application, which are within the scope of the claims.

[0039] Example 1

[0040] Referring to Fig. 1, the present application provides an intelligent construction method for a hardware equipment platform of a substation, comprising: Figures 1 to 4 Constructing a standardized hardware equipment base platform, and uniformly managing hardware equipment data and models;

[0041] Building an intelligent operation and maintenance system, adopting an online infrared temperature measurement combined with manual temperature inspection, collecting all hardware temperature data of the substation, setting multiple temperature thresholds for real-time early warning, identifying heat hazards through trend analysis, and focusing on monitoring the hazards;

[0042] Building an intelligent maintenance system, standardizing operation processes and fault diagnosis, automatically collecting hardware equipment resistance and torque parameters through a mobile terminal and uploading them, pushing standard operation cards according to the "ten-step method", combining intelligent wearables for digital operation, establishing a full-cycle data traceability for maintenance, and providing diagnostic support relying on a case library;

[0043] Building a hardware digital twin model, integrating three-dimensional visualization and temperature simulation, constructing a three-dimensional model, mapping two-dimensional and three-dimensional models of hardware equipment, positioning the hardware equipment, and predicting temperature rise in combination with load and environmental temperature;

[0044] Applying artificial intelligence technology, dynamically rating hardware based on multi-dimensional data in "green / yellow / red" three colors, and intelligently recommending the optimal maintenance strategy in combination with a fault library.

[0045] As shown in Fig. 1,

[0046] Figure 1 ​As shown, the standardized fitting equipment basic platform is built, taking the standardized data model as the core, by formulating the "Fitting Equipment Ledger Data Model Specification", the key parameters of the fitting equipment such as number, type, material, current-carrying capacity, etc. are uniformly managed to ensure the standardization and normalization of these parameters, thereby laying a solid foundation for the data governance of the entire platform; on this basis, a visual platform is built which deeply integrates two-dimensional models with ledger, operation, and maintenance data. This platform can intuitively present the spatial distribution of fitting equipment and realize real-time linkage analysis of multi-dimensional information, providing visual support for decision-making. At the same time, a mobile terminal standardized data collection and preprocessing mechanism is built to control the standardization and quality of detection data entry from the source, ensuring the integrity and accuracy of the data, and laying a solid foundation for subsequent intelligent analysis. Multi-level temperature thresholds are set to analyze and process the real-time collected data, and when the equipment temperature exceeds the set threshold, the system immediately sends a real-time warning signal to remind the operation and maintenance personnel to pay attention to the equipment status

[0047] The intelligent operation and maintenance system monitors the temperature of the key parts of the fitting equipment in the substation in real time and continuously through online infrared temperature measurement equipment, and obtains the temperature changes during the operation of the equipment. At the same time, manual inspection personnel are arranged to carry portable temperature measurement equipment and conduct regular temperature measurement of the equipment according to the preset inspection route and period, supplementing the deficiencies of online monitoring equipment and ensuring comprehensive coverage of the temperature data of the fitting equipment in the whole station. Multi-level temperature thresholds are set to analyze and process the real-time collected data, and when the equipment temperature exceeds the set threshold, the system immediately triggers a real-time warning signal of the corresponding threshold to remind the operation and maintenance personnel to pay attention to the equipment status. The intelligent operation and maintenance system also has a trend analysis function, which identifies abnormal temperature trends of the equipment by analyzing historical temperature data, discovers potential heating risks in advance, and marks the equipment with potential risks as key monitoring objects to increase the monitoring frequency and inspection frequency, ensuring that the potential risks can be handled in time and the safe and stable operation of the equipment is ensured.

[0048] The intelligent maintenance system is built, which automatically collects the resistance and torque parameters of the fitting equipment through mobile terminals, guides the standardized operation process, and assists the operation through intelligent wearables, realizing digital closed-loop management of the whole process of maintenance data. The intelligent maintenance system mainly includes mobile equipment maintenance, standardized operation process, equipment maintenance data management and control, and fault diagnosis.

[0049] The mobile equipment maintenance relies on the precise sensing ability of live detection instruments and the standardized fitting equipment basic platform, deeply develops mobile terminal data entry applications, realizes automatic collection and one-key uploading of parameters such as resistance and torque of fitting equipment, and constructs a data entry whole-process management mechanism to avoid data errors and omissions, greatly improving the efficiency of equipment measurement and the timeliness and accuracy of data processing.

[0050] The standardized maintenance procedures address routine maintenance tasks such as fitting breakage and re-leading, and direct resistance testing. The intelligent maintenance system automatically pushes standardized maintenance record sheets and work instruction cards to ensure a standardized and orderly work process. Once abnormal fittings are detected, the State Grid Corporation's "Ten-Step Method" standard procedure for fitting joint maintenance is strictly followed for precise handling. Simultaneously, relying on smart wearable devices and mobile terminals, and deeply integrating cutting-edge digital technologies such as video collaboration, image recognition, and voice interaction, the system implements standardized, digitalized, and intelligent control over the entire on-site operation process. This enables real-time monitoring, precise guidance, and efficient collaboration during the operation, comprehensively improving the quality and efficiency of maintenance work.

[0051] The fault diagnosis, such as Figure 2 As shown, it integrates core functions such as alarm parsing, fault location, and in-depth analysis. Relying on intelligent algorithms, it quickly analyzes abnormal data from hardware equipment and accurately locates fault points. Simultaneously, combined with a fault case library, it scientifically formulates maintenance strategies. It not only outputs preliminary analysis conclusions in real time but also intelligently provides tiered handling suggestions based on the severity of the fault, such as continuous monitoring or emergency power outages, providing a reliable basis for operation and maintenance decisions. The fault case library includes the "Hardware Equipment Overheating Defect Library," the "Hardware Equipment Fault Case Library," and the "Hardware Equipment Knowledge Base." The "Hardware Equipment Overheating Defect Library" and the "Hardware Equipment Fault Case Library" are compiled by deeply mining hardware operating data, systematically sorting out hardware overheating defects and fault cases, and closely integrating them with on-site operation and maintenance practices. The "Hardware Equipment Knowledge Base" is formed by comprehensively collecting hardware technical specifications, industry regulations, product manuals, and drawings, and systematically integrating them. The fault case library constructs a comprehensive knowledge system covering theoretical knowledge, practical experience, and technical standards.

[0052] The building hardware digital twin model includes multi-dimensional data fusion linkage, hardware high-fidelity three-dimensional modeling, and hardware temperature field simulation. The multi-dimensional data fusion linkage achieves deep linkage of data and models by integrating multi-dimensional data such as basic account books and operating parameters, ensuring real-time interaction and accurate mapping of information. The hardware high-fidelity three-dimensional modeling establishes a two-way mapping mechanism between two-dimensional models and three-dimensional models, labels the same physical feature points in the two-dimensional model and the three-dimensional digital twin model of the hardware equipment, obtains the accurate positions of the two-dimensional pixel coordinate system (u, v) and the three-dimensional coordinate system (X, Y, Z), calculates the conversion relationship through an orthogonal projection matrix, establishes a mathematical mapping model, and projects any point on the two-dimensional model to the corresponding position in the three-dimensional space through model back projection, breaking through the management bottleneck of hardware point positioning difficulty, and realizing global overview of hardware spatial distribution and second-level positioning of specific points. The hardware temperature field simulation uses temperature field simulation technology in digital twin to simulate the heat generation and transmission process of hardware equipment under the action of current thermal effect and environmental heat dissipation, dynamically generates the temperature field distribution of hardware equipment under different working conditions, traces the temperature change curve of the key part based on the simulation results, deduces the future temperature trend of the part combined with the heat accumulation law, and identifies the overheating risk points that may be caused by local heat concentration in advance, providing forward-looking data support for operation and maintenance decision-making.

[0053] The application of artificial intelligence technology includes state evaluation and intelligent operation and maintenance strategy. The state evaluation, as shown in Figure 3 , comprehensively considers the real-time temperature, temperature rise change, line power fluctuation, and historical temperature and temperature rise data of the hardware equipment, strictly follows the "DL / T 664-2016 Infrared Diagnosis Application Specification for Live Equipment", constructs a multi-dimensional equipment state evaluation model, scientifically judges the equipment operating state, and assigns "green code, yellow code, and red code" to the hardware state, thereby further developing differentiated monitoring and control of the hardware. The intelligent operation and maintenance strategy, as shown in Figure 4 , based on the equipment state evaluation conclusion and fault diagnosis result, deeply fuses the equipment defect risk level analysis, links the maintenance strategy database, accurately matches, recommends the optimal operation and maintenance project, type, and time scheme, and dynamically generates a scientific and reasonable operation and maintenance plan. Through this mechanism, the whole-chain closed-loop management of hardware equipment from hazard identification to accurate disposal is realized, the pertinence and planning of maintenance operation are effectively improved, and the operation and maintenance of hardware are promoted to the direction of lean and intelligent.

[0054] Embodiment two

[0055] Please refer to Figures 1 to 4 , based on embodiment one, the application further provides a substation hardware equipment platform intelligent construction system, which comprises:

[0056] A hardware standardization module is used to construct a standardized hardware equipment basic platform and uniformly manage hardware equipment data and models.

[0057] Temperature monitoring module for building intelligent operation and maintenance system, adopts online infrared temperature measurement and artificial temperature detection, full coverage collection of temperature data of all station fittings, and sets multi-level temperature threshold for real-time early warning, identifies heat hazards through trend analysis, and monitors the hidden trouble place;

[0058] Intelligent maintenance module for building intelligent maintenance system, standardizing operation process and fault diagnosis, automatically collecting and uploading the resistance and torque parameters of the fitting equipment through the mobile terminal, pushing the standard operation card according to the "ten-step method", combining with intelligent wear for digital operation, establishing the whole cycle data tracing of maintenance, and providing diagnosis support relying on the case library;

[0059] Digital twin module for building fitting digital twin model, integrating three-dimensional visualization and temperature simulation, building three-dimensional model, positioning the fitting equipment position by mapping two-dimensional model and three-dimensional model of fitting equipment, and combining load and environmental temperature for temperature rise prediction;

[0060] Intelligent evaluation module applies artificial intelligence technology, based on multi-dimensional data, dynamically evaluates the fitting as "green / yellow / red", and intelligently recommends the optimal maintenance strategy combined with the fault library.

[0061] As shown in Figure 1 , in the fitting standardization module, the standardization fitting equipment basic platform is built, taking the standardized data model as the core, by formulating the "fitting equipment account data model specification", the key parameters of fitting equipment such as number, type, material, current carrying capacity are uniformly managed, to ensure the standardization and normalization of these parameters, thus laying a solid foundation for data governance of the whole platform; on this basis, a visual platform is built which deeply integrates two-dimensional model and account, operation, maintenance data, which can intuitively present the spatial distribution of fitting equipment and realize real-time linkage analysis of multi-dimensional information, providing visual support for decision-making. At the same time, the mobile terminal standardization data acquisition and preprocessing mechanism is built, which controls the standardization and quality of detection data entry from the source, ensures the integrity and accuracy of data, and lays a solid foundation for subsequent intelligent analysis. Multi-level temperature threshold analyzes and processes the real-time collected data, when the equipment temperature exceeds the set threshold, the system immediately sends a real-time warning signal to remind the operation and maintenance personnel to pay attention to the equipment state

[0062] In the temperature monitoring module, the intelligent operation and maintenance system performs real-time and continuous temperature monitoring on key parts of the hardware equipment in the substation through online infrared temperature measurement equipment, and obtains temperature changes in the equipment operation process. At the same time, manual inspection personnel are arranged to carry portable temperature measurement equipment, and to perform periodic temperature measurement on the equipment according to a preset inspection route and period, to supplement the deficiencies of the online monitoring equipment and ensure comprehensive coverage of the hardware temperature data in the whole station; a plurality of temperature thresholds are set, the collected data are analyzed and processed, and when the equipment temperature exceeds the set threshold, the system immediately triggers a real-time warning signal of the corresponding threshold to remind the operation and maintenance personnel to pay attention to the equipment state. The intelligent operation and maintenance system also has a trend analysis function, which identifies abnormal change trends of the equipment temperature by analyzing historical temperature data, discovers potential heating hazards in advance, and marks the equipment with potential hazards as a key monitoring object to increase the monitoring frequency and inspection frequency, so that the hazards can be handled in time and the safe and stable operation of the equipment is ensured.

[0063] In the intelligent maintenance module, the intelligent maintenance system is constructed, the straight resistance, torque parameters, standardized operation process guidance and intelligent wearable auxiliary operation of the hardware equipment are automatically collected through a mobile terminal, and digital closed-loop management of the maintenance data throughout the whole process is realized. The intelligent maintenance system mainly includes equipment maintenance operation mobilization, maintenance standard operation process, equipment maintenance data management and control and fault diagnosis.

[0064] The equipment maintenance operation mobilization relies on the precise sensing ability of the live detection instrument and the standardized hardware equipment basic platform, deeply develops a mobile terminal data entry application, realizes automatic collection and one-key uploading of the straight resistance, torque and other parameters of the hardware equipment, and constructs a data entry whole-process management mechanism to avoid data errors and omissions, and greatly improves the equipment measurement efficiency and the timeliness and accuracy of data processing.

[0065] The maintenance standard operation process standardization is aimed at routine maintenance work such as hardware joint repair and straight resistance testing, and the intelligent maintenance system automatically pushes the standardized maintenance record table and the operation guidance card to ensure that the operation process is standardized and orderly. Once abnormal hardware is found, the “ten-step method” standard process of the hardware joint maintenance of the State Grid Corporation is strictly followed for accurate disposal. At the same time, relying on intelligent wearable devices and mobile terminals, the front-end digital technologies such as video collaboration, image recognition and voice interaction are deeply integrated to implement whole-process standardized, digital and intelligent management and control of the on-site operation, realize real-time monitoring, accurate guidance and efficient collaboration of the operation process, and comprehensively improve the quality and efficiency of the maintenance operation.

[0066] The fault diagnosis, for example, Figure 2As shown, the core functions of alarm analysis, fault location, and deep analysis are integrated, and the intelligent algorithm is used to quickly analyze and judge the abnormal data of the fitting device and accurately locate the fault point. At the same time, combined with the fault case library, the maintenance strategy is scientifically formulated, which can not only output the preliminary analysis conclusion immediately, but also intelligently give graded disposal suggestions such as continuous tracking and monitoring or emergency power-off treatment according to the fault severity, providing reliable basis for operation and maintenance decision. The fault case library includes a fitting device heating defect library, a fitting device fault case library, and a fitting device knowledge base. The fitting device heating defect library and the fitting device fault case library are prepared by closely combining the field operation and maintenance practice, and the fitting device knowledge base is formed by systematically integrating the fitting technical specifications, industry regulations and systems, product manuals and drawing materials. The fault case library builds a full-dimensional knowledge system covering theoretical knowledge, practical experience, and technical standards.

[0067] In the digital twin module, the construction of the fitting digital twin model includes multi-dimensional data fusion linkage, fitting high-fidelity three-dimensional modeling, and fitting temperature field simulation. Multi-dimensional data fusion linkage integrates multi-dimensional data such as basic account and operation parameters to achieve deep linkage between data and model, ensuring real-time interaction and accurate mapping of information. Fitting high-fidelity three-dimensional modeling establishes a bidirectional mapping mechanism between two-dimensional and three-dimensional models, labels the same physical feature points in the two-dimensional model and the three-dimensional digital twin model of the fitting device, obtains the accurate positions of the two-dimensional pixel coordinate system (u, v) and the three-dimensional coordinate system (X, Y, Z), calculates the conversion relationship through the orthogonal projection matrix, establishes a mathematical mapping model, and projects any point on the two-dimensional model to the corresponding position in the three-dimensional space through model back projection, breaking through the management bottleneck of multiple fitting points and difficult positioning, realizing global overview of fitting space distribution and second-level positioning of specific points. Fitting temperature field simulation uses temperature field simulation technology in digital twin to simulate the heat generation and transmission process of the fitting device under the action of current thermal effect and environmental heat dissipation, dynamically generates the temperature field distribution of the fitting device under different working conditions, traces the temperature change curve of the key parts based on the simulation results, deduces the future temperature trend of the part combined with the heat accumulation law, and identifies the overheating risk points that may be caused by local heat concentration in advance, providing forward-looking data support for operation and maintenance decision.

[0068] In the intelligent evaluation module, the application of artificial intelligence technology includes state evaluation and intelligent operation and maintenance strategy. The state evaluation, such as Figure 3As shown, the real-time temperature, temperature rise change, line power fluctuation, and historical temperature and temperature rise data of the fitting equipment are comprehensively considered, a multi-dimensional equipment state evaluation model is constructed by strictly following the "DL / T 664-2016 Infrared Diagnosis Application Specification for Live Equipment", and the running state of the equipment is scientifically judged, so as to assign "green code, yellow code and red code" to the fitting state, thereby further developing differentiated monitoring and control of the fitting. Figure 4 As shown, based on the equipment state evaluation conclusion and the fault diagnosis result, the equipment defect risk level analysis is deeply fused, the maintenance strategy database is linked, the optimal operation and maintenance project, type and time scheme are accurately matched and recommended, and a scientific and reasonable operation and maintenance plan is dynamically generated. Through the mechanism, the whole-chain closed-loop management of the fitting equipment from hidden danger identification to accurate disposal is realized, the pertinence and planning of the maintenance operation are effectively improved, and the operation and maintenance of the fitting are promoted to the lean and intelligent direction.

[0069] The computer equipment of the application comprises a memory, a processor and a computer program stored on the memory and executable on the processor, and the processor implements the steps of the above method when executing the computer program.

[0070] The computer readable storage medium of the application has a computer program stored thereon, and the computer program is executed by the processor to implement the steps of the above method.

Claims

1. A method for intelligent construction of a platform for substation hardware equipment, characterized in that, The application comprises the following steps: A standardized hardware equipment basic platform is constructed to manage hardware equipment account data model; the hardware equipment data model comprises hardware number, type, material, and current carrying capacity; An intelligent operation and maintenance system is constructed to collect hardware temperature data of the substation in full coverage and set multiple temperature thresholds for real-time early warning, identify heat hazards through trend analysis, monitor the hazards, construct an intelligent maintenance system, automatically collect hardware equipment direct resistance and torque parameters through a mobile terminal and upload them, push standard operation cards, combine intelligent wearables to perform digital operation, establish a full-cycle data traceability of maintenance, and provide fault diagnosis support relying on a case library; A hardware digital twin model is built, three-dimensional visualization and temperature simulation are integrated, a three-dimensional model is constructed, the position of the hardware equipment is located by mapping the two-dimensional model and the three-dimensional model of the hardware equipment, and temperature rise is predicted in combination with load and environmental temperature; Artificial intelligence technology is applied to dynamically rate the hardware in "green / yellow / red" three colors based on multi-dimensional data, and the optimal maintenance strategy is intelligently recommended in combination with the fault library. The standardized hardware equipment basic platform is constructed to input data from a mobile terminal and standardize the data, a two-dimensional model is established, the two-dimensional model is associated with the standardized hardware equipment account data, operation data, and maintenance data after standardization, and the standardized account data, operation data, and maintenance data of the hardware equipment are displayed on the platform.

2. The substation hardware equipment platform intelligent construction method of claim 1, characterized in that, The hardware digital twin model comprises:

3. The substation hardware equipment platform intelligent construction method of claim 1, wherein, A three-dimensional digital twin model is constructed, which is dynamically associated with hardware account data and operation data; a two-dimensional-three-dimensional space mapping technology is adopted to mark the same physical feature points in the two-dimensional model and the three-dimensional digital twin model of the hardware equipment, obtain the accurate positions of the two-dimensional pixel coordinate system (u, v) and the three-dimensional coordinate system (X, Y, Z), calculate the conversion relationship through an orthogonal projection matrix, establish a mathematical mapping model, and project any point on the two-dimensional model to the corresponding position in the three-dimensional space through the model; In combination with power load and environmental temperature parameters, a temperature field simulation technology in digital twin is used to simulate the heat generation and transmission process of the hardware equipment under the current thermal effect and environmental heat dissipation effect, dynamically generate the temperature field distribution of the hardware equipment under different working conditions, track the temperature change curve of the key parts based on the simulation results, deduce the future temperature trend of the parts in combination with the heat accumulation law, and identify the overheating risk points that may be caused by local heat concentration in advance. The artificial intelligence technology is applied to dynamically rate the health status of the hardware in "green / yellow / red" three colors based on the temperature, current, and historical operation and maintenance data of the hardware; 4. The substation hardware equipment platform intelligent construction method of claim 1, wherein According to the rating results of the hardware, differential detection is performed, the optimal operation and maintenance scheme is intelligently recommended in combination with the state evaluation results and the fault diagnosis model, and relying on the defect risk library and the maintenance strategy library, the optimal operation and maintenance scheme is intelligently recommended, including maintenance items, types, and periods. The application comprises the following steps:

5. A substation hardware equipment platform intelligent construction system, characterized in that, A hardware standardization module is used to construct a standardized hardware equipment basic platform to manage hardware equipment account data model; the hardware equipment data model comprises hardware number, type, material, and current carrying capacity; ​ The temperature monitoring module is used to build an intelligent operation and maintenance system, collect temperature data of the fittings in the transformer substation in full coverage, set multiple temperature thresholds for real-time early warning, identify heat hazards through trend analysis, monitor the hazards, and identify heat hazards through trend analysis. The intelligent maintenance module is used to build an intelligent maintenance system, automatically collect the direct resistance and torque parameters of the fittings through the mobile terminal, upload the parameters, push the standard operation card, perform digital operation in combination with the intelligent wear, establish a full-cycle data traceability of the maintenance, and provide fault diagnosis support relying on the case library. The digital twin module is used to build a fitting digital twin model, fuse three-dimensional visualization and temperature simulation, build a three-dimensional model, map the two-dimensional model and the three-dimensional model of the fitting device, locate the position of the fitting device, and predict the temperature rise in combination with the load and environmental temperature. The intelligent evaluation module applies artificial intelligence technology, performs three-color dynamic rating of the fittings based on multi-dimensional data, and intelligently recommends the optimal maintenance strategy in combination with the fault library.

6. The substation hardware equipment platform intelligent construction system of claim 5, wherein, In the fitting standardization module, the standardization fitting device basic platform is built, data is input from the mobile terminal, and the data is standardized. The two-dimensional model is established, the two-dimensional model is associated with the fitting device account data, operation data, and maintenance data after standardization, and the account data, operation data, and maintenance data of the fitting device after standardization are displayed on the platform.

7. The substation hardware equipment platform intelligent construction system of claim 5, wherein, In the digital twin module, the fitting digital twin model comprises: A three-dimensional digital twin model is built, which is dynamically associated with the fitting account data and operation data. A two-dimensional-three-dimensional space mapping technology is used to mark the same physical feature points in the two-dimensional model and the three-dimensional digital twin model of the fitting device, obtain the accurate positions of the two-dimensional pixel coordinate system (u, v) and the three-dimensional coordinate system (X, Y, Z), calculate the conversion relationship through the orthogonal projection matrix, establish a mathematical mapping model, and project any point on the two-dimensional model to the corresponding position in the three-dimensional space through the model. In combination with the power load and environmental temperature parameters, the temperature field simulation technology in the digital twin is used to simulate the heat generation and transmission process of the fitting device under the current thermal effect and environmental heat dissipation effect, dynamically generate the temperature field distribution of the fitting device under different working conditions, track the temperature change curve of the key parts based on the simulation results, deduce the future temperature trend of the parts in combination with the heat accumulation law, and identify the overheating risk points that may be caused by local heat concentration in advance. 8.The substation hardware equipment platform intelligent construction system of claim 5, characterized in that, In the intelligent evaluation module, the artificial intelligence technology is applied to perform three-color dynamic rating of the health status of the fitting based on the temperature, current, and historical operation data of the fitting. According to the rating results of the fitting, the state evaluation results and the fault diagnosis model are combined, the defect risk library and the maintenance strategy library are relied on, and the optimal operation and maintenance scheme is intelligently recommended, including the maintenance items, types, and periods.

9. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to realize the steps of the method in any one of claims 1 to 4.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the method in any one of claims 1 to 4.

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